There is a general need for a moving platform to quickly and effectively identify, track, and geolocate radio frequency (RF) emitters that are located in the vicinity of its pathway. For example, improvised explosive devices (IEDs) are often detonated by remote control. Although the radio equipment associated with an IED itself might, generally, only operate in a receive mode, such radio equipment may nevertheless “leak” RF energy from embedded oscillators and the like. Such RF energy is often in the form of continuous wave (CW) energy.
FIG. 1 depicts a setting for describing RF emitter proximity identification from the perspective of a moving vehicle. As shown, a vehicle 100 is moving at a certain speed on a path/road 110. An RF emitter 120 is distance D away from the road. Variables r and θ are the range and bearing, respectively, from the vehicle 100 to the RF emitter 120, and the vehicle 100 is distance X away from the RF Emitter 120 on the path 110. Conventional approaches, such as Direction Finding (DF) and Geolocation (GEO) methods, are commonly used to identify, track, and geolocate various sources of radio transmissions. DF is the process of obtaining the direction of arrival (DoA) bearings of radio signal emitters. GEO is the process of determining, either directly or indirectly based on DF estimates and/or other measures, the locations of emitter(s) of interest. DF and GEO techniques, which have been researched over the last fifty years, are mostly understood. The theory and applications of DF/GEO are well described in the open literature and, as such, need not be further described herein.
As is well-known, DF and GEO procedures for identifying and/or locating RF emitters are usually based on energy/amplitude comparison, interferometric, time-of-arrival (TOA), time-difference-of-arrival (TDOA), and other antenna null-steering approaches. These approaches usually demand special antennas, close-tolerance amplitude/phase RF receiver components, enhanced receiver dynamic range, and expanded processing bandwidth. DF/GEO systems can calculate the direction of arrival (DOA) of a particular RF emitter using an array of spatially displaced antennas or rotating antenna. Nearly all DF algorithms require that signals from multiple antennas are received and routed to multiple signal processors synchronously. These signal processors are then used to compare the amplitude/energy, phase, and TOA/TDOA from the various signals to derive the DOA and then location of the RF emitter.
Unfortunately, a moving platform usually has very limited space and/or less than desirable conditions to deploy special antennas that require well-controlled directionality and/or high-precision antenna patterns. Furthermore, these conventional DF and GEO approaches require the use of close-tolerance receiver/processing components and extensive processing resources, which may not be cost-effective and/or feasible for a mobile platform. Therefore, prior devices based on conventional DF and GEO approaches can not effectively or economically identify, track, and geolocate RF emitters from a moving platform.
More specifically, some key challenges for conventional DF and GEO approaches include:
(1) The requirement for coherent sampling of multiple antenna inputs. Most DF/GEO algorithms require high-precision coherent or synchronous Analog-to-Digital (A/D) Conversion sampling of all input signals so that phase/timing information is maintained.
(2) The complex data flow and throughput required between A/D converters and processors, as well as between the processors themselves. For instance, in DF systems, blocks of samples are synchronously digitized, where the block size may be a run time programmable parameter. Samples are time-tagged and then sent to a processor where a fast Fourier transform (FFT) is applied (i.e., front end processing). FFT results from one processor are then distributed to all the other processors for comparison and further calculation (i.e., backend processing). Final results are then sent to the host processor from where they may be geolocated, displayed, and/or transmitted across the communications network for further non-real-time processing.
(3) The potential requirement for additional pre-processing of raw digitized data before undergoing an FFT by the processors and/or post-processing of the FFT results. The raw data have to be filtered, decimated, and run through threshold level monitors for subsequent signal processing.
In light of the foregoing, there is a need to find different or alternative approaches that can quickly and efficiently identify and geolocate RF emitters in the field.